Total joint replacement (TJR) surgery decreases pain and increases functional mobility for patients with joint disease. As primary TJRs are implanted in patients who are younger, heavier, and more active, increases in TJR revision rates are expected. Polyethylene wear has been identified as a leading cause of TJR failure;therefore preclinical wear analysis has an essential role in the design process. Preclinical analysis of TJRs requires accurate joint contact force data which are difficult to obtain. A confounding issue is that variation in patient gait and activities results in different contact forces and corresponding polyethylene wear. It is likely that TJR wear simulators do not represent all TJR patients, but it is unrealistic to suggest that more than one set of input data be used for wear simulators to account for such variation. A validated mathematical model which calculates contact forces and allows variation of input data could add valuable insight for preclinical testing. We propose to extend our previous modeling methods to accurately calculate contact forces for TJR patients. Our methodology allows for variation in muscle activation levels to account for the full range of physiologic muscle activity and results in a solution space of contact forces rather than one profile. The proposed research will result in a model that can provide accurate contact forces and be sensitive enough to discern differences in TJR contact forces under a variety of loading conditions. The long-term objective is to provide additional information to aid the design of joint replacements which will help improve implant longevity. Our overall hypothesis is that a novel parametric model of the combined lower limb will constrain the solution space more effectively than isolated hip and knee models when compared to in vivo forces from instrumented joint replacements. We propose three aims to investigate our overall hypothesis. In the first aim we will validate our mathematical model. With the second aim we will compare the solution space of contact forces calculated with both models. In aim three we will investigate a relevant clinical application by comparing contact forces calculated with the new model for two total knee replacement patient cohorts. Relevance to Public Health: We propose to develop a new mathematical model of the lower limb to calculate joint contact forces for joint replacement patients. The model will be able to provide joint contact forces for variable patient gait and activities which are not otherwise available. Because of the increasing rate of total joint failures requiring revision surgery, our long-term aim is to help improve implant longevity by providing contact forces to supplement information provided by total joint simulators.